graph – Page 3 – Andrew Fairless, Ph.D.

What I Read: demystifying graph deep learning

By Andrew Fairless on August 30, 2021August 17, 2021

https://ericmjl.github.io/essays-on-data-science/machine-learning/graph-nets/ An attempt at demystifying graph deep learningEric Ma “There are a ton of great explainers of what graph neural networks are. However, I find that a lot of themContinue readingWhat I Read: demystifying graph deep learning

What I Read: Geometric, Deep Learning

By Andrew Fairless on August 16, 2021July 22, 2021

https://towardsdatascience.com/geometric-foundations-of-deep-learning-94cdd45b451d?gi=d7fa7307aa63 Geometric foundations of Deep LearningGeometric Deep Learning is an attempt for geometric unification of a broad class of ML problems from the perspectives of symmetry and invariance. These principlesContinue readingWhat I Read: Geometric, Deep Learning

What I Read: Difficulty of Graph Anonymisation

By Andrew Fairless on March 27, 2021March 7, 2021

https://www.timlrx.com/blog/tracetogether-and-the-difficulty-of-graph-anonymisation Timothy Lin@timlrxxSunday, February 7, 2021TraceTogether and the Difficulty of Graph Anonymisation “The word “anonymised data” seems to convey a certain sense of certainty that user information cannot be back-derived.Continue readingWhat I Read: Difficulty of Graph Anonymisation

What I Read: Why I’m lukewarm on graph neural networks

By Andrew Fairless on March 10, 2021March 7, 2021

https://www.singlelunch.com/2020/12/28/why-im-lukewarm-on-graph-neural-networks/ Why I’m lukewarm on graph neural networksMatt RangerFebruary 16, 2020 “I’m only lukewarm on Graph Neural Networks (GNNs)…. I think some progress can come of this research, but we’reContinue readingWhat I Read: Why I’m lukewarm on graph neural networks

What I Read: Introduction to Graph Neural Networks

By Andrew Fairless on February 23, 2021April 3, 2021

https://blog.exxactcorp.com/a-friendly-introduction-to-graph-neural-networks/ Deep LearningA Friendly Introduction to Graph Neural NetworksMarketing, November 11, 2020 “Graph neural networks (GNNs) belong to a category of neural networks that operate naturally on data structured asContinue readingWhat I Read: Introduction to Graph Neural Networks

What I Read: Approximate Nearest Neighbor Search in Vespa

By Andrew Fairless on February 21, 2021January 26, 2021

https://blog.vespa.ai/approximate-nearest-neighbor-search-in-vespa-part-1/ Approximate Nearest Neighbor Search in Vespa – Part 1Geir StorliPrinciple Vespa Engineer “Searching for the nearest neighbors of a data point in a high dimensional vector space is anContinue readingWhat I Read: Approximate Nearest Neighbor Search in Vespa

What I Read: HuggingFace Transformers

By Andrew Fairless on February 18, 2021January 18, 2021

https://medium.com/georgian-impact-blog/how-to-incorporate-tabular-data-with-huggingface-transformers-b70ac45fcfb4 How to Incorporate Tabular Data with HuggingFace TransformersGeorgianOct 23 “At Georgian, we find ourselves working with supporting tabular feature information as well as unstructured text data. We found thatContinue readingWhat I Read: HuggingFace Transformers

What I Read: Attention with Performers

By Andrew Fairless on February 7, 2021January 11, 2021

https://ai.googleblog.com/2020/10/rethinking-attention-with-performers.html Rethinking Attention with PerformersFriday, October 23, 2020Posted by Krzysztof Choromanski and Lucy Colwell, Research Scientists, Google Research “To resolve these issues, we introduce the Performer, a Transformer architecture withContinue readingWhat I Read: Attention with Performers

What I Read: What Color Is This? Part 2

By Andrew Fairless on February 3, 2021January 8, 2021

https://multithreaded.stitchfix.com/blog/2020/10/13/what-color-is-this-part-2/ What Color Is This? Part 2Blog post by Dan TasseDan TasseOctober 13, 2020 – San Francisco, CAWhat Color Is This, Part 2: The Computational Parts “We have to findContinue readingWhat I Read: What Color Is This? Part 2

What I Read: automatic differentiation with graphs

By Andrew Fairless on January 30, 2021January 5, 2021

https://ai.facebook.com/blog/a-new-open-source-framework-for-automatic-differentiation-with-graphs A new open source framework for automatic differentiation with graphsOctober 8th, 2020 “Just as PyTorch provides a framework for automatic differentiation with tensors, GTN provides such a framework forContinue readingWhat I Read: automatic differentiation with graphs

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